Abstract

Calculation of excess disease burden for As exposed populations is becoming increasingly important to enable quantitative estimation of the impacts of various As mitigation options. There are several methods by which such calculations may be carried out. In this study, two methods, recently applied to estimating groundwater As-related health risks in southern Asia, to estimate disease burden arising from lung, bladder and liver cancer from As exposure for an As-effected area of West Bengal have been compared. Both utilized calculated distributions of exposure of the studied population to As from groundwater. Method (I) then entailed calculating disease burden by combining published background rates for death and disability adjusted life years (DALYs) and standard mortality ratios (SMRs) for excess health impacts related to As exposure, whilst for Method (II). disease burden from As exposure was estimated using the basic DALY formula, combined with incidence rates based on the NRC multistage Weibull model. Dose-response data for both methods were based on Studies in Taiwan.
When the same dose-response model was used for both methods, the two methods were broadly comparable, agreeing to within a factor of 4 for both deaths and DALYs. Much larger differences, up to a factor of 40, were noted when SMRs from different previous studies were utilized by Method (1). Thus, the death and DALYs calculations are most sensitive to the choice of dose-response model and less so to the calculation method. The differences are also partly ascribed to different background (i.e. for As non-exposed populations) rates for lung, bladder and liver cancers between Chakdha block and Taiwan. However, the differences also highlight some of systematic uncertainties in the application of epidemiological studies in one part of the world to another, emphasizing that accurate health risk estimates are likely to be better obtained by large scale systematic surveys of health outcomes in the study population. Irrespective of the comparability of the results of the two methods, it is noted that the lack of detailed consideration of confounding factors such as genetic polymorphisms, smoking and dietary habits, and, in particular, exposure to As through other routes, notably ingestion of As-bearing rice, may significantly impact on the accuracy of the results obtained by either method.